Ge Precision Healthcare LLC

Tim Sprenger

Suchandrima Banerjee

Arnaud Guidon

Robert Marc Lebel

Ersin Bayram

Daniel Vance Litwiller

Xinzeng Wang

Gaohong G Wu

Jaemin Shin

Baolian Yang

Douglas Link

Systems and methods are provided for a slice-ahead inversion sequence for jointly acquiring non-inverted and inverted contrast. In one example, a method for a magnetic resonance imaging (MRI) system includes acquiring k-space data with the MRI system according to a slice-ahead inversion sequence that jointly generates a contrast without inversion preparation and one or more inversion contrasts for a plurality of slices in a scan volume of a subject, wherein the k-space data comprises first k-space data of the contrast without inversion preparation acquired during one or more non-inversion repetitions and second k-space data of the one or more inversion contrasts acquired during one or more inversion repetitions, wherein a repetition time for each of the one or more non-inversion repetitions and one or more inversion repetitions is constant, and reconstructing one or more images from the k-space data.

Systems and methods for slice-ahead inversion for magnetic resonance imaging

A computer-implemented method and system for performing magnetic resonance diffusion weighted imaging of an object includes generating, via a processor, a diffusion weighted imaging sequence where all diffusion gradients are allocated into N groups such that all imaging slices are acquired for all the diffusion gradients corresponding to a group of the N groups back-to-back in A*TR, wherein N is two or larger, wherein Ais a number of diffusion gradients of each group of the N groups and TR is repetition time, and wherein in each TR every diffusion gradient of the group of the N groups is applied at least once. The computer-implemented method and system also includes acquiring, via the processor, imaging slices for multiple groups of the N groups utilizing the diffusion weighted imaging sequence during a scan of the object utilizing a magnetic resonance imaging scanner.

System and method for diffusion group cycling

A computer-implemented method of correcting phase and reducing noise in magnetic resonance (MR) phase images is provided. The method includes executing a neural network model for analyzing MR images, wherein the neural network model is trained with a pair of pristine images and corrupted images, wherein the corrupted images include corrupted phase information, the pristine images are the corrupted images with the corrupted phase information reduced, and target output images of the neural network model are the pristine images. The method further includes receiving MR images including corrupted phase information, and analyzing the received MR images using the neural network model. The method also includes deriving pristine phase images of the received MR images based on the analysis, wherein the derived pristine phase images include reduced corrupted phase information, compared to the received MR images, and outputting MR images based on the derived pristine phase images.

Systems and methods of generating robust phase images in magnetic resonance images

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Munich, Germany

Tim Sprenger